On Using Backpropagation for Speech Texture Generation and Voice Conversion

Inspired by recent work on neural network image generation which rely on backpropagation towards the network inputs, we present a proof-of-concept system for speech texture synthesis and voice conversion based on two mechanisms: approximate inversion of the representation learned by a speech recognition neural network, and on matching statistics of neuron activations between different source and target utterances. Similar to image texture synthesis and neural style transfer, the system works by optimizing a cost function with respect to the input waveform samples. To this end we use a differentiable mel-filterbank feature extraction pipeline and train a convolutional CTC speech recognition network. Our system is able to extract speaker characteristics from very limited amounts of target speaker data, as little as a few seconds, and can be used to generate realistic speech babble or reconstruct an utterance in a different voice.Comment: Accepted to ICASSP 201

Sequence-to-Sequence Models Can Directly Translate Foreign Speech

We present a recurrent encoder-decoder deep neural network architecture that directly translates speech in one language into text in another. The model does not explicitly transcribe the speech into text in the source language, nor does it require supervision from the ground truth source language transcription during training. We apply a slightly modified sequence-to-sequence with attention architecture that has previously been used for speech recognition and show that it can be repurposed for this more complex task, illustrating the power of attention-based models. A single model trained end-to-end obtains state-of-the-art performance on the Fisher Callhome Spanish-English speech translation task, outperforming a cascade of independently trained sequence-to-sequence speech recognition and machine translation models by 1.8 BLEU points on the Fisher test set. In addition, we find that making use of the training data in both languages by multi-task training sequence-to-sequence speech translation and recognition models with a shared encoder network can improve performance by a further 1.4 BLEU points.Comment: 5 pages, 1 figure. Interspeech 201

Effect of variations in atelectasis on tumor displacement during radiation therapy for locally advanced lung cancer

Purpose Atelectasis (AT), or collapsed lung, is frequently associated with central lung tumors. We investigated the variation of atelectasis volumes during radiation therapy and analyzed the effect of AT volume changes on the reproducibility of the primary tumor (PT) position. Methods and materials Twelve patients with lung cancer who had AT and 10 patients without AT underwent repeated 4-dimensional fan beam computed tomography (CT) scans during radiation therapy per protocols that were approved by the institutional review board. Interfraction volume changes of AT and PT were correlated with PT displacements relative to bony anatomy using both a bounding box (BB) method and change in center of mass (COM). Linear regression modeling was used to determine whether PT and AT volume changes were independently associated with PT displacement. PT displacement was compared between patients with and without AT. Results The mean initial AT volume on the planning CT was 189 cm3 (37-513 cm3), and the mean PT volume was 93 cm3 (12-176 cm3). During radiation therapy, AT and PT volumes decreased on average 136.7 cm3 (20-369 cm3) for AT and 40 cm3 (−7 to 131 cm3) for PT. Eighty-three percent of patients with AT had at least one unidirectional PT shift that was greater than 0.5 cm outside of the initial BB during treatment. In patients with AT, the maximum PT COM shift was ≥0.5 cm in all patients and \u3e1 cm in 58% of patients (0.5-2.4 cm). Changes in PT and AT volumes were independently associated with PT displacement (P \u3c .01), and the correlation was smaller with COM (R2 = 0.58) compared with the BB method (R2 = 0.80). The median root mean squared PT displacement with the BB method was significantly less for patients without AT (0.45 cm) compared with those with AT (0.8cm, P = .002). Conclusions Changes in AT and PT volumes during radiation treatment were significantly associated with PT displacements that often exceeded standard setup margins. Repeated 3-dimensional imaging is recommended in patients with AT to evaluate for PT displacements during treatment. Summary This study analyzed 12 patients with atelectasis and 10 patients without atelectasis who underwent repeat 4-dimensional fan beam computed tomography during radiation therapy. Patients with atelectasis had significantly greater tumor displacements than patients without atelectasis, and these tumor displacements often exceeded standard setup margins. Patients with atelectasis may benefit from repeated 3-dimensional imaging during radiation therapy and possible replanning for large tumor displacements

Evaluation of Image Registration Accuracy for Tumor and Organs at Risk in the Thorax for Compliance With TG 132 Recommendations

Purpose To evaluate accuracy for 2 deformable image registration methods (in-house B-spline and MIM freeform) using image pairs exhibiting changes in patient orientation and lung volume and to assess the appropriateness of registration accuracy tolerances proposed by the American Association of Physicists in Medicine Task Group 132 under such challenging conditions via assessment by expert observers. Methods and Materials Four-dimensional computed tomography scans for 12 patients with lung cancer were acquired with patients in prone and supine positions. Tumor and organs at risk were delineated by a physician on all data sets: supine inhale (SI), supine exhale, prone inhale, and prone exhale. The SI image was registered to the other images using both registration methods. All SI contours were propagated using the resulting transformations and compared with physician delineations using Dice similarity coefficient, mean distance to agreement, and Hausdorff distance. Additionally, propagated contours were anonymized along with ground-truth contours and rated for quality by physician-observers. Results Averaged across all patients, the accuracy metrics investigated remained within tolerances recommended by Task Group 132 (Dice similarity coefficient \u3e0.8, mean distance to agreement \u3c3 \u3emm). MIM performed better with both complex (vertebrae) and low-contrast (esophagus) structures, whereas the in-house method performed better with lungs (whole and individual lobes). Accuracy metrics worsened but remained within tolerances when propagating from supine to prone; however, the Jacobian determinant contained regions with negative values, indicating localized nonphysiologic deformations. For MIM and in-house registrations, 50% and 43.8%, respectively, of propagated contours were rated acceptable as is and 8.2% and 11.0% as clinically unacceptable. Conclusions The deformable image registration methods performed reliably and met recommended tolerances despite anatomically challenging cases exceeding typical interfraction variability. However, additional quality assurance measures are necessary for complex applications (eg, dose propagation). Human review rather than unsupervised implementation should always be part of the clinical registration workflow

Interobserver Reliability in Describing Radiographic Lung Changes After Stereotactic Body Radiation Therapy

Purpose Radiographic lung changes after stereotactic body radiation therapy (SBRT) vary widely between patients. Standardized descriptions of acute (≤6 months after treatment) and late (\u3e6 months after treatment) benign lung changes have been proposed but the reliable application of these classification systems has not been demonstrated. Herein, we examine the interobserver reliability of classifying acute and late lung changes after SBRT. Methods and materials A total of 280 follow-up computed tomography scans at 3, 6, and 12 months post-treatment were analyzed in 100 patients undergoing thoracic SBRT. Standardized descriptions of acute lung changes (3- and 6-month scans) include diffuse consolidation, patchy consolidation and ground glass opacity (GGO), diffuse GGO, patchy GGO, and no change. Late lung change classifications (12-month scans) include modified conventional pattern, mass-like pattern, scar-like pattern, and no change. Five physicians scored the images independently in a blinded fashion. Fleiss\u27 kappa scores quantified the interobserver agreement. Results The Kappa scores were 0.30 at 3 months, 0.20 at 6 months, and 0.25 at 12 months. The proportion of patients in each category at 3 and 6 months was as follows: Diffuse consolidation 11% and 21%; patchy consolidation and GGO 15% and 28%; diffuse GGO 10% and 11%; patchy GGO 15% and 15%; and no change 49% and 25%, respectively. The percentage of patients in each category at 12 months was as follows: Modified conventional 46%; mass-like 16%; scar-like 26%; and no change 12%. Uniform scoring between the observers occurred in 26, 8, and 14 cases at 3, 6, and 12 months, respectively. Conclusions Interobserver reliability scores indicate a fair agreement to classify radiographic lung changes after SBRT. Qualitative descriptions are insufficient to categorize these findings because most patient scans do not fit clearly into a single classification. Categorization at 6 months may be the most difficult because late and acute lung changes can arise at that time

Regionale Innovationspolitik: Konzentration auf Hightech kann in die Irre führen

Die Bewertung der Innovationsfähigkeit von Regionen hat vor dem Hintergrund des verschärften regionalen Wettbewerbs um Fördermittel an Bedeutung gewonnen. Zur Bestimmung des regionalen Innovationspotentials werden oftmals einfach zu erhebende Indikatoren wie die Anzahl der Patentanmeldungen aus einer Region oder die innovationsrelevante Beschäftigung herangezogen. Diese Indikatoren sind jedoch stark auf forschungsintensive Branchen fokussiert und vernachlässigen, dass es neben wissenschaftsbasierter Innovation auch die weniger akademische Form der ingenieursbasierten Innovation gibt. Dies birgt die Gefahr fehlgeleiteter innovationspolitischer Maßnahmen, bei denen die Heterogenität von Branchen nicht ausreichend berücksichtigt wird. Solche Strategien sind daher wenig geeignet, regionale Innovationspotentiale - und damit die regionale Wettbewerbsfähigkeit - effektiv zu fördern.Regional innovation capacity, Regional innovation policy, Cluster, Knowledge bases

Transmission-line resonators for the study of individual two-level tunneling systems

Parasitic two-level tunneling systems (TLS) emerge in amorphous dielectrics and constitute a serious nuisance for various microfabricated devices, where they act as a source of noise and decoherence. Here, we demonstrate a new test bed for the study of TLS in various materials which provides access to properties of individual TLS as well as their ensemble response. We terminate a superconducting transmission-line resonator with a capacitor that hosts TLS in its dielectric. By tuning TLS via applied mechanical strain, we observe the signatures of individual TLS strongly coupled to the resonator in its transmission characteristics and extract the coupling components of their dipole moments and energy relaxation rates. The strong and well-defined coupling to the TLS bath results in pronounced resonator frequency fluctuations and excess phase noise, through which we can study TLS ensemble effects such as spectral diffusion, and probe theoretical models of TLS interaction